| Name: Jason Mohoney | NetID: mohoney2 | Email<EMAIL_ADDRESS>|
| Name: Joshua Stephani | NetID: jstephani2 | Email<EMAIL_ADDRESS>|
| Name: Max Vrany | NetID: mvrany | Email<EMAIL_ADDRESS>|
Videos are just a sequence of images. A panorama can be created from a sequence of images. We are simply trying to create a panorama from a video that features a pan sequence. We will need to figure out which frames will need to be extracted, how to extract them, what processing will be needed to optimize the extracted frames and how to merge them.
Figuring out which frames need to be extracted is critical. We need to make sure that we have enough frames to assemble a complete image. (This may involve deciding how much missing areas are acceptable.) At the same time, extracting too many frames could result in too much redundant information and could increase computational complexity beyond an acceptable level.
Processing extracted frames may provide additional details in the images that may improve the quality and performance of the merging process.
The design of the merging process will be critical to ensure the process completes in a timely manner and accurately assembles the extracted frames.
We have selected a paper [1] that implements a solution to the problem we would like to solve. A high level overview of the authors’ implementation is as follows:
In addition to an implementation to follow, the paper gives a set of open questions we could seek to answer.
Minimally we would like to complete the implementation described in the paper and if enough time, tackle one of the open questions listed above.
[1] Minchen Zhu, Weizhi Wang, Binghan Liu, and Jingshan Huang, “Efficient video panoramic image stitching based on an improved selection of harris corners and a multiple-constraint corner matching,” PloS one, vol. 8, no. 12, pp. e81182, 2013.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0081182&type=printable
| Task | Description | Date |
|---|---|---|
| Create Webpage | Add proposal and wiki. | 9/26 |
| Initialize Project | Plan necessary components, dependencies, tasks, and divide workloads | 10/1 |
| Input Preprocessing | Implement the preprocessing portion of the project. | 10/8 |
| Feature Extraction / Matching | Implement image feature extraction and match features in pairs. | 10/18 |
| Stitching | Implement the stitching of images from the matched feature pairs. | 10/29 |
| Minimum Viable Product | MVP should be able to take two images and stitch them together in one. | 10/31 |
| Code Cleanup / Additional Features | Perform testing, bug fixes, and code cleanup. Add the functionality for stitching more than two images. Tackle an open question. | 10/31 - 11/21 |
| Code Completion | Project code completion. | 11/21 |
| Results Gathering | Gather results based on different input videos / images. | 11/30 |
| Final Presentation | Present project and results to class. | 12/3 |
| Complete Webpage | Post project details on website along with results, code, etc... | 12/12 |


Introduction
What is it?
A simple (aka Noddy) collection of object orientated numerical routines written in C++, aimed at undergraduate projects and starting graduate students. In the current version, the test/example cases solve (amongst others):
- Two-dimensional parabolic problems ( eg., the unsteady boundary-layer equations ).
- Boundary-value ODE problems ( eg., the Karman rotating-disk, Blasius boundary-layer and other similarity solutions ).
- Arc-length continuation of problems involving limit points ( eg., the Karman rotating disk equations, Falkner-Skan equation, the plane Poiseuille flow linear neutral curve. ).
- One-dimensional eigenvalue problems ( eg., the (bi-)harmonic equation, Orr-Sommerfeld equation ) solved both directly and via local methods.
- One-dimensional hyperbolic problems ( eg., Sod's shocktube problem, linear acoustic waves with reflection in non-uniform medium, shallow water eqiations ).
- Two-dimensional hyperbolic problems ( eg., compressible Euler problems, linear acoustic waves, shallow water eqiations ).
- Initial-boundary-value problems ( eg., the heat diffusion equation in 1D, and the unsteady Karman rotating-disk equations ).
- Initial-value problems ( eg., the Lorenz equations ).
- Poisson problems in Cartesian and cylindrical geometries.
A breakdown of examples into groups is found under the 'Modules' link above. Alternatively, a complete list of examples can be found at this link Tests
The library provides:
- Both dense vector and sparse vector classes (including the usual vector operations).
- Dense , banded and sparse matrix classes.
- A class for ODE IVPs with 4th-order Runge-Kutta(-Fehlberg) method(s).
- A class for ODE BVPs with second-order finite-difference methods and adaptive refinement.
- A class for ODE EVPs with second-order finite-difference methods.
- A class for IBVPs with second-order methods in both ‘space’ and ‘time’.
- A class for Two dimensional parabolic problems with a second-order box scheme.
- Classes for both 1-D and 2-D hyperbolic problems via central scheme algorithms.
- 2-D Poisson objects (Cartesian and axisymmetric cylindrical polars).
- vector Newton iteration classes.
- Arc-length continuation solvers exist for Residual objects and boundary value problems.
- An ability to link to selected BLAS, LAPACK and PETSc routines via a simplified API (these currently include the real/complex generalised eigenproblem solvers, dense/banded/sparse LU solvers.).
What is it for?
It exists for two reasons:
- It's an introduction/framework for final-year undergraduate project students or graduate students.
- Just for fun.
I think it needs a CppNoddy::foo<bar> class
Feel free to add something. If you're an undergraduate looking for a final-year project or an MSc. student and have an idea of something to include (or wish to redesign something that I did in a stupid way), then let me know.
Content created by R.E. Hewitt, 2007. MIT license.


Recently I had been reading a lot about the various RCs around and as Iíve always been curious about drugs. I started smoking pot at 12 then went through amphetamine, Ecstacy, benzodiazapines, crack cocaine, cocaine, methadone, LSD, mushrooms and ended up taking heroin and getting hooked for some years, so Iíve had experience with both uppers and downers. But as Iíd kicked the heroin habit I decided to try these Rcs.
Firstly I tried Mephedrone, swallowing 250mg in a 'bomb' before going to a house party. After 15min I could feel a slight restlessness which got stronger as time went on. By the 1hr mark I was defiantly feeling something. The closest I could compare it to was amphetamines but it wasnít anywhere near as aggressive. On speed I just HAD to move, even if sitting I had to jiggle my leg but with mephedrone it didnít seem to be like that at all although I was still strongly stimulated. I could sit and be still, no compulsion to move myself if I didnít want to, where on speed I felt I ďhadĒ to. I also had an overwhelming need to talk and be frank with people.
The other thing I noticed, I had a great empathy with people, not as strong as with MDMA, but personally I felt MDMA to be too overwhelming in its empathy giving qualitys. With mephedrone it seemed I had the right balance for me. After 3hrs I decided to top up as I seemed to have crashed all of a sudden with no warning, which was a shock as with other things used its always tapered off, so I swallowed another 250mg and this took me back to where I was before. As the night went on I found it very easy to talk to people I knew and didnít know at the party which is normally hard for me and as night turned to day (I swallowed my first bomb at 6pm, my second at 9pm) I decided to leave for home, which was around 5.30am. I felt sleep was impossible for me so I stayed awake, not feeling any come down but just generally drained, due to no sleep. Then next night I slept fine and wanted to repeat this experience.
My next experience with mephedrone was drastically different and is maybe a cautionary tale about mixing drugs, at least mephedrone and cocaine. The amount was the same, 250mg swallowed around 6pm then out to friends house for a party. I smoked some pot and talked away feeling the same empathy and stimulation. This time though a friend brought out some grams of cocaine which some of us proceeded to take. Alltogether, over the night (from 7pm to 5am) I had gone through 2 grams myself pretty much, but the 2 drugs didnít mix well at all.
Where the last time I was clearheaded and knew what I wanted to say, this time I kept forgetting what I wanted to say, I was jabbering a lot and falling drastically behind in conversation. An example of this is how a friend and I were trying to remember the word penicillin as we were talking about allergies, but we couldnít think of the word. Some hrs later it popped into my head and I shouted ďpenicillin!!Ē even though the friend I was talking to about this earlier was long gone. Evidently the mix of both drugs had impaired my mind greatly so I donít think Iíll do this again, as although it did feel good at the time, looking back though it was too much on my brain.
So in conclusion I think Mephedrone is a very good stimulant, it has all the good qualities of amphetamine, like stimulation, increased awareness and confidence but with the added bonus of a feeling of empathy and euphoria, which speed doesnít have.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


[gecode-users] multi-dimensional bin-packing constraint - bin capacities
Christian Schulte
cschulte at kth.se
Tue Nov 18 10:14:47 CET 2014
Hi Kish,
Yes, when I added this I thought exactly the same. However, I decided to
include the c argument to avoid confusion: the values of c (or as you say
the upper bound on the load variables) actually defines how well the
constraint is propagated. So what I tried to avoid by including c is that
users first post the binpacking constraint and only then adjust the load
variables...
I know, matter of taste.
Cheers
Christian
--
Christian Schulte, Professor of Computer Science, KTH,
www.gecode.org/~schulte/
-----Original Message-----
From: users-bounces at gecode.org [mailto:users-bounces at gecode.org] On Behalf
Of Kish Shen
Sent: Monday, November 17, 2014 6:52 PM
To: users at gecode.org
Subject: [gecode-users] multi-dimensional bin-packing constraint - bin
capacities
Hi,
I am updating ECLiPSe's Gecode interface to Gecode 4.3, and I am adding
support for the multi-dimensional bin-packing constraint.
I have a small question about the arguments for the constraint:
binpacking(home, d, l, b, s, c)
has the capacities argument c that is not found in the 1-D bin-packing
constraint:
binpacking(home, l, b, s)
My understanding is that for this form of the constraint, c is implicitly
specified by l, the loads, i.e. the domains of each bin is specified by the
domain in the load variable for that bin.
It seems to me that the values for c is also implicitly specified for the
multi-dimensional case, and can be derived from l, as the maximum domain
value of all the variables in l for each dimension. I am thinking of
providing the constraint in this form so that it looks more like the 1-D
version. Does this make sense?
Cheers,
Kish
_______________________________________________
Gecode users mailing list
users at gecode.org
https://www.gecode.org/mailman/listinfo/gecode-users
More information about the users
mailing list


#include <helpbase.h>
Inheritance diagram for THelpFile::
Public Methods | |
| THelpFile (fpstream &s) | |
| virtual | ~THelpFile () |
| THelpTopic* | getTopic (int) |
| THelpTopic* | invalidTopic () |
| void | recordPositionInIndex (int) |
| void | putTopic (THelpTopic *) |
Public Attributes | |
| fpstream* | stream |
| Boolean | modified |
| THelpIndex* | index |
| long | indexPos |
Definition at line 287 of file helpbase.h.
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Undocumented. Definition at line 326 of file helpbase.h. |
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Undocumented. Definition at line 330 of file helpbase.h. |
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Undocumented. Definition at line 322 of file helpbase.h. |
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An app called Keynote Tweet has been around (in various working and non-working states) since the late 2000’s and let users auto-tweet images of their Keynote slides during a presentation to a hashtag or stream. Google released the Slides API this year and one of the API methods allows you to get a thumbnail of the image which can then be sent to other applications. You can see an example of this in a slideshow now by going to View > HTML View. It opens a tab with slide images embedded in plain HTML formatting. Since we can now get the image, we can start to push them out to other platforms with Google Apps Script.
This post is going to be technical in nature and is really meant as a proof-of-concept. I’ll explain some of the shortcomings of this implementation in context. The code is broken up into several chunks and the entire source is posted to GitHub.
First, the Slides API has to be enabled in the Google Cloud Console. Once that’s done, getting the thumbnails is pretty easy.
Off the bat, the API doesn’t have event triggers like the Forms, Sheets, or Docs. I wanted each slide to be tweeted as the presentation advanced, so I needed a custom presentation view. To get this to work, I wrote up a web app presentation window served by Google’s HtmlService
.
This simple HTML page requests and displays the slides from an array created by the backend. There are some controls that hide on the bottom of the screen and a position indicator in the top right. Hover the mouse and they’ll pop up for interaction.
The initial page load for the web app varies depending on the size of the presentation. The request for slides on line 37 fires as soon as the document loads in the browser. The loading GIF is replaced by the slides when they’re returned.
The slide thumbnails are returned as 1600×900 pixel PNGs, so they’re big, which increases load time. There is no way to specify the size of the image returned at this point.
Each slide is sent as an image on a tweet as they show is advanced and has posted
class added to prevent multiple tweets of the same slide. The “previous” button does not trigger a tweet in the event you go backwards.
I used Martin Hawksey’s TwtrService library to connect my Twitter account. He has a detailed post on how to connect and use the library, so I’m not going to go through that here. This is also where the second major snag comes up.
Google recommends not using libraries in production code because they can negative impact on script runtime. This is especially apparent on the first slide in this script – it times out frequently (3 of 5 times?) and I’m not sure why. Subsequent slides come in between 20-50 seconds, which isn’t terrible, considering the image size being uploaded. But, if you’re a fast talker, this won’t be able to keep up unless some kind of queueing is implemented.
To do this without a library, the OAuth flow needs to be incorporated into the main script. It’s beyond my ability at the moment, so if you’d like to contribute that component and help this run as a standalone app, you can do submit a pull request on the GitHub repo.
Sending the tweet is actually a two-step process. First, the slide thumbnail is posted and then the media_id
assigned is attached to the tweet. This is all done on the Google Apps Script side of the code to account for security considerations.
Google’s thumbnail is generated and hosted on their server, so I used the UrlFetchApp
to request the content as a blob
. This is serialized data that can be passed on to Twitter’s image hosting service.
Once the image is uploaded, we can take the returned media_id
string and attach it to a tweet. The Twitter API object for a tweet has a number of options, but all I’m using is status
(what you’re saying) and media_ids
, which takes the image ID string from the upload.
Right now, the string is hard-coded into the script. This could be set via the Apps Script UI tools if this gets turned into an AddOn at some point if I can speed it up.
Twitter requires a high degree of authorization for posting. I tried implementing the OAuth flow without using a library to speed up performance, but I couldn’t get it to work. TwtrService
stores the app credentials for the OAuth flow and has both an upload
and post
method that make the tweeting easy. But, performance varies for 20 seconds to as long as 300.
The app works, which was exciting to put together and see. It’s a function that would be great in a number of situations and implementation will only get better as the Slides API improves. I’d love to work with someone with more experience to speed the API calls up significantly by including all the necessary authentication in the main script rather than in a library. If you’d be willing to contribute, the source code is on GitHub.
If you’d like to play with it, you can either copy all the files from GitHub or copy and paste the separate embeds here into an empty project. Add postTweet
and getThumbnails
to the code below.
—
Mountain Bluebird flickr photo by Andrej Chudy shared under a Creative Commons (BY-NC-SA) license
Written on November 15th, 2017 by Brian Bennett Categorized in: All Code Technology
Leave a comment


"Life is a fashion show, And the world is your runway.""
Coco Chanel
Coco Chanel is a fashion designer icon, born on August 19,1883 in Saumur, France.


So you think you are brave enough to face the beasts and warriors outside the town gates?
Maybe you should avoid wandering out there in the night...Unless you want to face some really dangerous creatures
{{unit.name}}


DesirabilityUpdater(cityMap: CityMap)
This class is responsible for going over each zoned tile and figuring out the "Desirability score"... in other words how badly people want to live there...
cityMap - The map that we pass in...
cityMap


Toggle navigation
Dora
Submit
Settings
Dropdown
Action
Another action
Something else here
Separated link
New scan


asa2pdf(1f) - [FILE FILTER] Convert text files with/without ASA carriage control to an Adobe PDF file. (LICENSE:PD)
Synopsis
Description
Usage
Options
Environment Variables
Examples
See Also
Author
License
asa2pdf -o output_filename -i input_filename -g gray_scale_shade -b lines_alternately_shaded -d dashcode -s top_middle_page_label -t top_left_page_label -P # add page numbers -l lines_per_page -f font_name -S columns_to_shift_data -N # add line numbers -H page_height -W page_width -u points_per_unit -L left_margin -R right_margin -B bottom_margin -T top_margin -help -version -show
Basically, asa2pdf(1) emulates a line printer that recognizes ASA carriage control. That is, it lets you convert ASCII text files using ASA carriage control into Adobe "clear text" PDF files instead of a printed page.
The PDF is clear-text ASCII so that it is easy to still use other Unix/Linux utilities such as spell(1), diff(1), grep(1), .... on the output files.
To properly view the output requires a PDF processor (such as xpdf(1),acroread(1)/AcroRd32, gv(1) or ghostview(1), ...). Most modern systems can view, mail and print PDF files.
The default layout generates a landscape 132-column 60-line format with every other two lines shaded. A variety of switches are available to let you easily print files with no vertical carriage control, and in portrait mode too. There are options to use dashed lines instead of shading, to set different margins, and so on.
WHAT IS ASA CARRIAGE CONTROL?
The ASA carriage control standard was the first important formatting standard for printing and viewing text files. The standard was almost universally adapted by printer manufacturers of the time (and printers were a much more common output device than interactive displays).
Most commercial high-level programs at the time the standard was created were either FORTRAN or COBOL; so nearly all early FORTRAN output used ASA carriage control (ASA was the American Standards Association -- now ANSI). This FORTRAN/ASA association became so strong that the standard is sometimes referred to as the "Fortran carriage control standard" (FCC). Indeed, even though ASA is no longer commonly directly supported on desktop printers, it was part of the Fortran 90 standard (this was dropped in Fortran 2003 -- how a printer processes files is really not directly part of any programming language).
Times have changed, and the once nearly ubiquitous ASA standard is poorly supported on Unix and MSWindows machines in particular (Direct operating-system support of ASA files was once common, but is now rare).
But no alternative as simple has emerged for output files that truly replaces the ASA standard (although machine control characters (ctrl-H, ctrl-L, ...) have come close they have their own issues).
So many programs using ASA-based formatting have not been changed, and use commands like asa(1)/nasa(1), and fpr(1) to allow the files to be printed as desired but NOT to generally be viewed properly on-line, and printing itself is becoming less common.
So the problem isnt so much with ASA files, but that todays infrastructure does not support the format well. The asa2pdf(1) program bridges the gap by allowing you to still make and manipulate ASA files until you want to print or email them, at which time you can quickly convert them to an Adobe PDF file.
asa2pdf(1) reads input from standard input. By default the first character of each line is interpreted as a control character. Lines beginning with any character other than those listed in the ASA carriage-control characters table or in the list of extensions below are interpreted as if they began with a blank, and an appropriate diagnostic appears on standard error. The first character of each line is not printed.
ASA Carriage Control Characters
+------------+-----------------------------------------------+ | Character | | +------------+-----------------------------------------------+ | + | Do not advance; overstrike previous line. | | blank | Advance one line. | | null lines | Treated as if they started with a blank | | 0 | Advance two lines. | | - | Advance three lines (IBM extension). | | 1 | Advance to top of next page. | | all others | Discarded (except for extensions listed below)| +------------+-----------------------------------------------+Extensions
H Advance one-half line. R Do not advance; overstrike previous line. Use red text color G Do not advance; overstrike previous line. Use green text color B Do not advance; overstrike previous line. Use blue text color r Advance one line. Use red text color g Advance one line. Use green text color b Advance one line. Use blue text color ^ Overprint but add 127 to the ADE value of the character (ie., use ASCII extended character set)
-o outputfile Name of Adobe PDF output file to create -i inputfile Name of text file to read. Defaults to stdin.
The page size may be specified using -H for height, -W for width, and -u to indicate the points per unit (72 makes H and W in inches, 1 is used when units are in font points). For example:
-u 72 -H 8.5 -W 11 # page Height and Width in inches -T 0.5 -B 0.5 -L 0.5 -R 0.5 # margins (Top, Bottom, Left, Right)common media sizes with -u 1:
+-------------------+------+------------+ | name | W | H | +-------------------+------+------------+ | Letterdj (11x8.5) | 792 | 612 | (LandScape) | A4dj | 842 | 595 | | Letter (8.5x11) | 612 | 792 | (Portrait) | Legal | 612 | 1008 | | A5 | 420 | 595 | | A4 | 595 | 842 | | A3 | 842 | 1190 | +-------------------+------+------------+
-g 0.800781 gray-scale value for shaded bars ( 0 < g 1 ) 0 is black, 1 is white. -b 2 repeat shade pattern every N lines -d dashcode pattern The pattern is a series of integers defining an on-off sequence in user units used to create a dash pattern. A single digit "N" implies a pattern of "N N". (seems buggy)
-s top middle page label. -t top left page label. -P add page numbers to right corners
-l 60 lines per page -f Courier font names: Courier, Courier-Bold,Courier-Oblique Helvetica, Symbol, Times-Bold, Helvetica-Bold, ZapfDingbats, Times-Italic, Helvetica-Oblique, Times-BoldItalic, Helvetica-BoldOblique, Times-Roman, Courier-BoldOblique -S 0 right shift 1 for non-ASA files -N add line numbers
-version display version number -help display this help
o $IMPACT_TOP Will be printed in large red letters across the page top. o $IMPACT_GRAY sets the default gray-scale value, same as the -g switch.
Sample input:
> The numbers are plain underlined double-struck over-struck >+ __________ double-struck /////////// >R /////////// > abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789-=_+()*&^%$#@!\|[]{};:",.<>/?~ > >r red >g green >b blue > PRIMARY: >R red >G green >B blue > 1/2 line advance >H 1 >H 2 a-1 >H 3 Z >H 4 b > back to a normal lineSample commands:
# use non-ASA file to generate portrait mode with a dashed line under every line asa2pdf -S 1 -W 8.5 -H 11 -b 1 -d 2 4 1 -T 1 -B .75 -o paper.pdf < INFILE# banner on top env IMPACT_GRAY=1 IMPACT_TOP=CONFIDENTIAL asa2pdf -o paper.pdf < test.txt
# 132-column landscape asa2pdf -s LANDSCAPE -o paper.pdf <asa2pdf.c
# 132-column landscape with line numbers with dashed lines asa2pdf -s LANDSCAPE LINE NUMBERS -d 3 1 2 \ -N -T .9 -o paper.pdf <asa2pdf.c
# portrait 80-column non-ASA file with dashed lines asa2pdf -s PORTRAIT -S 1 -W 8.5 -H 11 -b 1 -d 2 4 1 \ -T 1 -B .75 -o paper.pdf < asa2pdf.c
# portrait 80-column with line numbers , non-ASA asa2pdf -s PORTRAIT LINE NUMBERS -l 66 -S 1 -W 8.5 -H 11 \ -b 1 -T 1 -B .75 -N -o paper.pdf < asa2pdf.c
# titling asa2pdf -d 1 0 1 -t "$USER" -b 1 -P -N -T 1 \ -s "asa2pdf.c" -o paper.pdf <asa2pdf.c
ALTERNATIVES TO ASA2PDF
About the only standard ASA support on Unix variants is that some contain the asa(1)/fpr(1) and nasa(1) commands for converting ASA text files into and from text files with machine control (MC) characters such as form-feed, backspace, carriage-return, .... Most personal printers will no longer properly print ASA files directly, but they will often correctly print files with simple MC characters (Note that the asa(1) command is referenced in the POSIX.2 standard).
Furthermore, if a printer does not directly support MC characters, text conversion utilities such as enscript(1) and a2ps(1) can often be used to print the files (usually by converting the files to PostScript or PCL). Such utilities support features such as titling, page numbering, and other useful options.
Programs like "Adobe Distiller" can convert text to a PDF; as well as editors such as OpenOffice. In fact, most modern document-formatting editors can read in an ASCII text file and save it as an Adobe PDF file.
HTML and PostScript/PDF and PCL files are the alternatives often incorporated to satisfy simple formatting criteria -- yet HTML is not printer-oriented; and PDF files are complex to write from a simple program, and PCL is vendor-specific and has few on-line viewers available for it.
Assuming converting the Fortran program to just write a plain ASCII file instead of an ASA file is not acceptable, More extensive flat-text formatting is available usingOther Unix commands that can be useful in working with plain text and MC character files are
o HTML, *roff and LaTex-related file formats o libraries for writing more sophisticated PostScript, PDF, and HTML/CSS files o XML files formatted using Cascading Style Sheet (CSS) files o RTF (Rich Text Format) files
pr(1) can be used to add page numbers and titles. expand(1) can remove tab characters fold(1),fmt(1) can be used to wrap the text cut(1) can let you trim or select columns cat -n can be used to add number lines paste(1) can be used to put files side-by-side.asa(1)/nasa(1), fpr(1), enscript(1), a2ps(1), and ps2pdf(1).
John S. Urban
Public Domain
| Nemo Release 3.1 | asa2pdf (1) | July 22, 2023 |


Friend Finder!
Take our survey about friend behavior and find your new best friend!
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{% extends "base_nav.html" %} {% load crispy_forms_tags %} {% block title %}
Verify the details for this workshop. Return to event page to edit other event details.


{% extends "base.html" %} {% block content %}
Did you ever wanted to organize a small BBQ and had to send around houndreds of mails to organize who brings what? Ever wanted to last-minute send your flat mate that he should bring milk from the groceries? I've got it makes it easy. Just create a list, share the ID and keep everybody updated on who brings what. No registration needed. It's dead simple.
{% endblock %}


Can't remember the sessions you want to go?
Location for each session are posted on [Sessions] tab
WMCI requests the presence of all Grade 12 students to participate in our Youth Symposium during Friday, May 13, 2016. The focus of our symposium is contemporary issues that face society today. We want to expose you to community issues and provide a platform for you to consider what type of actions you may be able to take as you enter the adult world. This morning we will be sharing information with you through stories, voices, and experiences.
Students need to select three sessions of interest using the sessions tab on this webpage. Based on your choices, we will provide you with a schedule of sessions that includes time and location at May 13. Following our opening ceremony, you will experience a unique learning opportunity that we hope makes you think, feel, and wonder.
You are the leaders of the future – what are you going to do to make Saskatoon, Saskatchewan, and the world a better place?
Your Name, Please give a space between firstname and lastname, Firstname first please


interface StandardData : DataModel
Interface that "standard" data model classes should implement.
See Also
com.hexanovate.familytree.database.manager.StandardDataManager
data class Person : StandardData, WithEvent, Comparable<Person>, Parcelable
Represents a member of the family. |


Popular Music Genres Introduction
Dec 16, 2019 • softrime
There are so many different types of music like Jazz, R&B, Blues etc. If you listen each one of these music several times, you may know what’s it like, but also, you don’t know why. So the motivation of this article is to describe popular music genres in a academic way. I’ll try to introduce each common music genre specifically. Some typical examples would be better. This is an interesting work. Keep doing.
1900s
Ragtime
- Instruments: Piano
- Ragtime was very popular towards the end of the 19th century and into the first two decades of 20th century. It’s a genre of musical composition for the piano, which is considered as a synthesis of European Classical Music and African Syncopation(切分音). Each hand doing something different. Left hand plays a rhythm section, which is a steady march-like succession(交替) of Bass Notes and Chords. The low notes mimic a tuba(大号) or other bass instruments. The chords communicates the harmony of the song. They also mimic a kick and snare drum pattern. Much of the difficulty comes from the fact that a stride left hand jumps around a lot. Moving nonstop from low register bass notes to middle register chords. The right hand is responsible for most the syncopation, as it plays syncopation melodies in a ‘ragged’ fasion(hence the name ‘ragtime’). To sum up, ragtime is composed from bass notes and chords of the left hands, and syncopation of the right hand. After accelerating the speed, here comes the ragtime~
Gospel
- Instruments: Singer
- Gospel music is a genre of Christian music. It is derived from religious chants of afro-american communities and pioneer of soul and R&B. The Gospel music is tuneful and easy to grasp. Its lyrics is mostly about religion. The use of chords is not complicated.
1910s
Tin Pan Alley
- Instruments: Piano, Singer, Orchestra
- Tin pan alley is the pioneer of the pop music. Many famous songs were born in this periods. Tin Pan Alley is the name of a district, where so many music producers located in. For chinese, the style of music in that time is like which in Old Shanghai(老上海). And I think Tin Pan Alley is more like today’s popular music.
Dixieland
- Instruments: String Bass, Tuba, Piano, Trumpet
- Dixieland Jazz (sometimes refered to as Hot Jazz or Traditional Jazz), is a style of jazz based on the music that developed in New Orleans. One of the first uses of the term “Dixieland” with reference to music was in the name of the band “Original Dixieland Jazz Band”. The definitive Dixieland sound is created when one instrument (usually the trumpet) plays the melody or a recognizable paraphrase or variation on it, and the other instruments of the ‘front line’ improvise around that melody. This creates a more polyphonic sound than the arranged ensemble playing of the big band sound.
1920s
Country Blues
- Instruments: Guitar, Singer
- Blues was born as a form of expression of black communities and outcasts. And country blues is one of the ealiest forms of blues music. It usually consists of a singer with a guitar. And sometimes the lyric is like the AAB pattern which is famous in blues. Also a maybe difference between early blues and hillbilly(country) is that the former is mainly performed by blacks while the latter whites.
Hillbilly
- Instruments: Guitar, Singer
- The Blue music can be found as far back as the 1920s, when the record industry created the marketing categories “race music” and “hillbilly music” to sell music by blacks for blacks and by whites for whites, respectively. At the time, there was no clear musical division between blues and country music. And hillbilly is more like the pioneer of the modern country music.
Boogie Woogie
- Instruments: Piano
- Boogie Woogie is generated by Tin Pan Alley piano composers in the style of blues. Actually it’s really like Ragtime for me. The main difference is that the left hand in Boogie Woogie plays a repeating stable bass pattern, and the right hand is more free and variant than ragtime. On the other hand, thay are both have the rhythm with a high and delight tempo.
Gipsy Jazz
- Instruments: Guitar, Violin
- Gipsy jazz is a style of jazz developed by the Romani guitarist “Django Reinhardt” in Paris during the 1930s. The absence of brass lead instruments and drums was a novelty in the jazz context. In my opinion, Gipsy Jazz is dominated by giutar, which is also like Flamenco guitar. And also there is no piano and drum.
1930s
Swing
- Instruments: Cello(Bass), Drums, Piano, Woodwind(木管乐器), Brass(铜管乐器)
- Swing music is a form of popular jazz music developed in the United States that dominated in the 1930s and 1940s. Swing played by a big band always make everybody dance. For a typical pattern, SWING is consisted with a walking bassline which is a steady quarter-note pulse(1/4), drums emphasis beats 2 and 4, piano glues the rhythm section, and a call-response riff section with woodwind and brass.
West Country/Swing
- Instruments: Guitar, Singer, Drums
- At this time, country music was inspired from the SWING. There are more dancable rhythm section in the country music with drums and beat pattern. It was still country music, and in my opinions, the most impressived feature of country music is the singing style of singer.


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ps.py documentation¶
ps module¶
This module contains facility classes and functions to access PowerSchool and change the XML data into a more workable format.
- class ps.Connection¶
Creates a temporary browser that connects to PowerSchool using HTTP.
>>> conn = Connection() >>> conn.login('http://powerschool.ausd.net', '12345', 'password') True >>> student = conn.get_student() >>> student.first_name "Johnny" >>> student.gpa "2.5"
- close()¶
Closes the browser instance.
- error = None¶
(string) error message from PowerSchool
- get_student()¶
Note
Must be logged in to work.
Create a student from the login information.
- get_xml()¶
Note
Must be logged in to work.
Downloads the XML data from PowerSchool and returns its contents.
- logged_in = None¶
(bool) returns whether Connection was able to log in
- login(url, username, password)¶
Logs into url with credentials username and password.
Parameters: - url (string) – PowerSchool URL to login into. ex. http://powerschool.ausd.net/
- username (string) – PowerSchool username (usually a Student ID#)
- password (string) – PowerSchool password
Returns: True if login was successful. Otherwise, False.
- student = None¶
(Student) a Student from the Connection
- xml_data = None¶
(string) downloaded XML data
- class ps.Student(loadstring=None)¶
A Student is a data structure that holds:
Field Type Description first_name (string) First name last_name (string) Last name gender (string) Gender (Male/Female) gpa (string) Grade point average courses (course[]) Courses A course is a dictionary containing:
Field Type Description name (string) Course name teacher (string) Course teacher (LastName, FirstName) letter_grade (string) Letter grade received (A, B, C, etc.) number_grade (string) Number grade received (percentage) in_progress (bool) Sees if course is to be included assignments (assn[]) Assignments categories (string[]) Categories of assignments for course An assn (assignment) is a dictionary containing:
Field Type Description name (string) Assignment name category (string) Category of assignment (test, project, etc.) due_date (string) Due date (Month/Day/Year format) score (float) Score gotten on assignment out_of (float) Total amount of points possible Parameters: loadstring (string) – XML data to load Student info - courses = None¶
(course[]) Course list
- filter_courses(cutoff_date)¶
Sets each course’s in_progress attribute to True if it is between cutoff_date and today.
Parameters: cutoff_date (datetime.date) – Courses between this day (inclusive) will be included.
- first_name = None¶
(string) First name
- gender = None¶
(string) Gender
- gpa = None¶
(string) Grade point average
- last_name = None¶
(string) Last name
- load(loadstring)¶
Loads a Student with XML data received from loadstring.
Parameters: loadstring (string) – XML data to load Student from
- to_excel()¶
Note
Requires that the Student has been loaded.
Returns: Creates a xlwt Workbook of the Student’s grades.
- to_json()¶
Note
Requires that the Student has been loaded.
Returns: Student in JSON format.
- z_to_json(strength=9)¶
Note
Requires that the Student has been loaded.
Does the same thing as to_json, but compresses the information with maximum strength before returning it.


Tancho Mihov
Nikolay Tornev
Software designers.Working with java,html,css.
© 2016 - Site Built By Tancho & Niki | IT Talents


--- layout: default meta_title: "Policies & FAQs | Blind Dog Yarns" meta_description: "Find order policies and frequently asked questions" open_graph_img: /assets/images/BlindDogYarns-vector-black.svg twitter_img: /assets/images/BlindDogYarns-vector-black.svg ---
Buyer is responsible for paying shipping. Shipping prices vary depending on item.
The time I need to prepare an order for shipping varies. For details, see individual items.
Buyers are responsible for return shipping costs. If the item is not returned in its original condition, the buyer is responsible for any loss in value. Questions about your order? Please contact me if you have any problems with your order.
I love working with you if you have an idea that you don't see on my site. Please send me a message with any ideas and we'll start a conversation.
Acrylic yarn does not felt and holds up well to washing and drying. Please wash on the gentle cycle and tumble dry low.
My handspun yarn is wool and will felt. For all items featuring my handspun yarn, hand washing and laying flat to dry is recommended.
The majority of the wool featured in my cowls and scarves is a fine Merino wool. Most of it is also hand dyed by me using environmentally friendly, low impact dyes. These dyes are heavy metal free which keeps toxic metals from entering the environment, particularly groundwater, throughout the life cycle of the dye and wool.


package andrewscurtis
Ordering
- Alphabetic
Visibility
- Public
- All
Type Members
- case class ACData (paths: Map[String, Stream[(FiniteDistribution[AtomicMove], FiniteDistribution[Moves])]], dir: String) extends ACresults with Product with Serializable
- class ACFileSaver extends FDSrc[(FiniteDistribution[AtomicMove], FiniteDistribution[Moves]), Param]
- case class ACStateData (states: Map[String, (FiniteDistribution[AtomicMove], FiniteDistribution[Moves])], dir: String) extends ACStates with Product with Serializable
Value Members
- object ACData extends Serializable
- object ACFileSaver
- object ACFlow
- object ACFlowSaver
- object ACevolution
- object AndrewsCurtis
- object AndrewsCurtisInterface
- object SimpleAcRun


Nick's Vim Cheatsheet
Add new binding
Download data
Github Repository
Helpful Resources
Web Cheatsheet This is based off TODO
Web Cheatsheet Site TODO
Web cheatsheet TODO
cheatsheet With Cross TODO
GitHub cheatsheet TODO
CDN cheatsheet (see comments) TODO
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pwd
OS/161 Reference Manual
Name
pwd - print working directory
Synopsis
/bin/pwd
Description
pwd prints the current working directory.
Requirements
pwd uses the following system calls:
pwd should function properly once the basic system calls assignment is
completed, except on filesystems or in directories that do not support
getcwd.
pwd should function properly in all directories of your filesystem
once the file system assignment is completed.


Our events are open to newbies, developers, managers, and organizations who are interested in Google's technologies or use them as part of their projects. Google Developer Groups (GDGs) are for developers who are interested in Google's developer technology; everything from the Android, App Engine, and Google Chrome platforms, to product APIs like the Maps API, YouTube API and Google Calendar API.
Email<EMAIL_ADDRESS>Website: gdgsetif.club
Meetup: meetup.com/GDG-Setif


|
Contextualization Tool
1.0
|
This is the model class of a MVC architecture on Contextualization Tool app. More...
#include <contextualizationmodel.h>
Signals | |
| void | stringsListChanged () |
| This signal is emited when a string is modified on model. | |
| void | imageChanged () |
| This signal is emited when the image of model is changed. | |
Public Member Functions | |
| ContextualizationModel (QString image="", QList< FirmwareString *> list=QList< FirmwareString *>()) | |
| Constructs a model. More... | |
| ~ContextualizationModel () | |
| Destroys the model. | |
| void | addString (const QString &id, const QString &value, const QString &description, const QString &maxLength, const QString &state, const bool selected) |
| Adds new string to the model. More... | |
| void | addString (FirmwareString *newString) |
| Adds new string to the model. More... | |
| void | addStrings (QList< FirmwareString *> &strings) |
| Adds new string to the model. More... | |
| bool | removeString (QString &id) |
| Removes string with the identifier received by parameter. More... | |
| bool | removeString (int pos) |
| Removes string that are in position received by parameter. More... | |
| void | removeAllStrings () |
| Removes all items from the firmware strings list. | |
| bool | selectString (const QString id) |
| Selects string with the identifier received by parameter. More... | |
| bool | unselectString (const QString id) |
| Unselects string with the identifier received by parameter. More... | |
| QList< QObject * > & | getStringsList () |
| Returns the firmware strings list. More... | |
| void | setImage (QString path) |
| Sets the image of the model. More... | |
| QString | getImage () |
| Returns the image associated to the model. More... | |
| bool | isEmpty () |
| Checks if the model is empty. More... | |
| bool | hasImage () |
| Returns true if the model has a valid image associated. More... | |
| bool | hasStrings () |
| Returns true if the model has any string. More... | |
| void | clear () |
| Empty the model. More... | |
| QString | toJson (QJsonDocument::JsonFormat format=QJsonDocument::Compact) |
| Returns the model converted to a JSON QString. More... | |
| QJsonObject | toJsonObject () |
| Returns the model converted to a #QJsonObject. More... | |
| ContextualizationModel & | operator= (ContextualizationModel &other) |
| Assigns other to this model and returns a reference to this model. More... | |
Static Public Member Functions | |
| static ContextualizationModel * | fromJson (QString &json) |
| Returns a ContextualizationModel initializated with the JSON string json. More... | |
| static ContextualizationModel * | fromJson (QByteArray &json) |
| Returns a ContextualizationModel initializated with the #QByteArray data json. More... | |
This is the model class of a MVC architecture on Contextualization Tool app.
Definition at line 23 of file contextualizationmodel.h.
| ContextualizationModel::ContextualizationModel | ( | QString | image = "" , |
| QList< FirmwareString *> | list = QList<FirmwareString *>() |
||
| ) |
Constructs a model.
Creates a model setting the image as the image received by parameter. Also adds to the model strings received in the list of the second parameter. If no parameters are received, create an empty model.
| image | File path of image to associate to the model. |
| list | List of strings to add on the model. |
Definition at line 13 of file contextualizationmodel.cpp.
| void ContextualizationModel::addString | ( | const QString & | id, |
| const QString & | value, | ||
| const QString & | description, | ||
| const QString & | maxLength, | ||
| const QString & | state, | ||
| const bool | selected | ||
| ) |
| void ContextualizationModel::addString | ( | FirmwareString * | newString | ) |
Adds new string to the model.
| newString |
Definition at line 42 of file contextualizationmodel.cpp.
| void ContextualizationModel::addStrings | ( | QList< FirmwareString *> & | strings | ) |
Adds new string to the model.
Adds all strings in the list received by parameter.
| strings | List of strings to add. |
Definition at line 49 of file contextualizationmodel.cpp.
| void ContextualizationModel::clear | ( | ) |
Empty the model.
Unsets the path of image and removes all items from the firmware strings list.
Definition at line 179 of file contextualizationmodel.cpp.
|
static |
Returns a ContextualizationModel initializated with the JSON string json.
If the JSON data received is not valid, return an empty model.
| json | String in JSON format to be converted. |
Definition at line 207 of file contextualizationmodel.cpp.
|
static |
Returns a ContextualizationModel initializated with the #QByteArray data json.
If the JSON data received is not valid, return an empty model.
| json | QByteArray in JSON format to be converted. |
< Release memory because of an error on json decode process.
Definition at line 214 of file contextualizationmodel.cpp.
| QString ContextualizationModel::getImage | ( | ) |
Returns the image associated to the model.
Definition at line 155 of file contextualizationmodel.cpp.
| QList< QObject * > & ContextualizationModel::getStringsList | ( | ) |
Returns the firmware strings list.
Definition at line 141 of file contextualizationmodel.cpp.
| bool ContextualizationModel::hasImage | ( | ) |
Returns true if the model has a valid image associated.
Definition at line 169 of file contextualizationmodel.cpp.
| bool ContextualizationModel::hasStrings | ( | ) |
Returns true if the model has any string.
Definition at line 174 of file contextualizationmodel.cpp.
| bool ContextualizationModel::isEmpty | ( | ) |
Checks if the model is empty.
The model is empty when there aren't any image in the model and the firmware strings list is empty. Return true if model is empty.
Definition at line 160 of file contextualizationmodel.cpp.
| ContextualizationModel & ContextualizationModel::operator= | ( | ContextualizationModel & | other | ) |
Assigns other to this model and returns a reference to this model.
| other | Model to be copied. |
Definition at line 269 of file contextualizationmodel.cpp.
| bool ContextualizationModel::removeString | ( | QString & | id | ) |
Removes string with the identifier received by parameter.
Returns true if the string removed succesfuly. Returns false if there are not any string with this identifer.
| id | Identifier of firmware string to remove. |
Definition at line 56 of file contextualizationmodel.cpp.
| bool ContextualizationModel::removeString | ( | int | pos | ) |
Removes string that are in position received by parameter.
Returns true if the string removed succesfuly. Returns false if is not a valid position.
| pos | Position of the string in list. |
Definition at line 75 of file contextualizationmodel.cpp.
| bool ContextualizationModel::selectString | ( | const QString | id | ) |
Selects string with the identifier received by parameter.
Returns true if the string selected succesfuly. Returns false if there are not any string with this identifer.
| id | Identifier of firmware string to remove. |
Definition at line 105 of file contextualizationmodel.cpp.
| void ContextualizationModel::setImage | ( | QString | path | ) |
Sets the image of the model.
| path | File path of the image. |
Definition at line 146 of file contextualizationmodel.cpp.
| QString ContextualizationModel::toJson | ( | QJsonDocument::JsonFormat | format = QJsonDocument::Compact | ) |
Returns the model converted to a JSON QString.
| format | Exit format of JSON. |
Definition at line 185 of file contextualizationmodel.cpp.
| QJsonObject ContextualizationModel::toJsonObject | ( | ) |
Returns the model converted to a #QJsonObject.
Definition at line 190 of file contextualizationmodel.cpp.
| bool ContextualizationModel::unselectString | ( | const QString | id | ) |
Unselects string with the identifier received by parameter.
Returns true if the string selected succesfuly. Returns false if there are not any string with this identifer.
| id | Identifier of firmware string to remove. |
Definition at line 123 of file contextualizationmodel.cpp.


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Smorgasbord of carbs from a local bakery in Madrid.
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Classic lattice blueberry pie, great for any occasion.
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Ridiculously smooth yet stretchy ice cream, in a range of unique flavors. Flushing/Chinatown Ice Cream Factory, NYC.
Smile!
End-of-meal fruits from Zenon Taverna, NYC.
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Spiraling alternative to an apple pie, or if one has run out of dough making a pie.
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{% extends "schedule/__base.html" %} {% block content %} {% if form.errors %}
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Protesters torch DR Congo mayor's office after massacre
by REUTERSIn Summary
- Violence by the ADF and a patchwork of militias and criminal bands near Congo’s borders with Uganda and Rwanda have regularly killed civilians and hampered efforts to eradicate a more than year-long Ebola outbreak.
Goma,
Protesters in the eastern Democratic Republic of Congo city of Beni set the town hall on fire on Monday after suspected Islamist rebels killed eight people in an overnight raid.
Rebels believed to belong to the Allied Democratic Forces (ADF) have killed more than 70 civilians in massacres since the Congolese army launched an offensive against them this month.
The police force tweeted a photo of the Beni mayor’s office with flames shooting from the window and thick black smoke billowing above.
“Security forces are working to re-establish public order,” it said.
Violence by the ADF and a patchwork of militias and criminal bands near Congo’s borders with Uganda and Rwanda have regularly killed civilians and hampered efforts to eradicate a more than year-long Ebola outbreak.
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The ADF has been operating near the Ugandan border for more than two decades. It is one of dozens of rebel groups active in the mineral-rich are-as where civil wars resulted in millions of deaths around the turn of the century.
Last week, suspected ADF militants killed at least 19 people, kidnapped others and torched a Catholic church.
Several ADF attacks have been claimed by Islamic State, but the extent of their relationship remains unclear.
The World Health Organization said last week that while the number of new Ebola cases in the ongoing outbreak, the second deadliest of all time, was down considerably, it was unable to stamp out the epidemic due to insecurity.


--- layout: post title: 'ISSI meeting photo opp: Lidar heads of state :-)' date: '2010-12-20T09:45:00.000-05:00' author: Bob Sica tags: modified_time: '2011-12-21T12:48:50.363-05:00' blogger_id: tag:blogger.com,1999:blog-736339229338318027.post-5390733180380863056 blogger_orig_url: http://blog.purplecrowlidar.ca/2010/12/issi-meeting-photo-opp-lidar-heads-of.html ---
Here’s a photo Boyan took of the ISSI NDACC lidar algorithm working group. After the marathon that is the AGU Fall Meeting, ISSI seems so long ago (except to my body which is rebelling against the latest time zone change). You can see some more snaps at here.


Welcome
I am a Computer Engineer, you can checkout my resume here. Resume
I usally waste my time doing cool projects.
You can checkout my projects on my resume, but if you want to get connect You can visit my LinkedIn, here: LinkedIn
Cheers!
Emperor@computer:~/Emperor/About_Me$


ISATTY
Section: Linux Programmer's Manual (3)
Updated: 2014-01-27
Index
Return to Main Contents
NAME
isatty - test whether a file descriptor refers to a terminal
SYNOPSIS
#include <unistd.h>
int isatty(int fd);
DESCRIPTION
The
isatty()
function tests whether
fd
is an open file descriptor referring to a terminal.
RETURN VALUE
isatty()
returns 1 if
fd
is an open file descriptor referring to a terminal;
otherwise 0 is returned, and
errno
is set to indicate the error.
ERRORS
- EBADF
-
fd
is not a valid file descriptor.
- EINVAL
-
fd
refers to a file other than a terminal.
POSIX.1-2001 specifies the error
ENOTTY
for this case.
ATTRIBUTES
Multithreading (see pthreads(7))
The
isatty()
function is thread-safe.
CONFORMING TO
SVr4, 4.3BSD, POSIX.1-2001.
SEE ALSO
fstat(2),
ttyname(3)
Index
- NAME
-
- SYNOPSIS
-
- DESCRIPTION
-
- RETURN VALUE
-
- ERRORS
-
- ATTRIBUTES
-
- Multithreading (see pthreads(7))
-
- CONFORMING TO
-
- SEE ALSO
-
This document was created by
man2html,
using the manual pages.
Time: 02:55:09 GMT, September 18, 2014


GhostMouse
This tool will allow you to pilot an automated cursor, while preventing the user from interactive with the page. It's useful for showing a user what to do during a tutorial.
To demonstrate, here's a nice little box you can draw in with your real mouse:
And here are some automated drawings that show a GhostMouse in action. The drawing area doesn't know anything special about these movements, GhostMouse just fires normal mouse events (and only mouse events, for now—no touch or pointer events).


Isar735.github.io
Miles Morland Foundation African Scholarship 2018/2019. Essay Service: Ma in creative writing prose Ma in creative writing prose at uea to write about chronological order research paper. For example, in so many prose writing creative in ma at uea less distractions. The Watchmaker of Filigree Street: Natasha Pulley. Learning And Studying And Writing: A DIY MA In Creative.
Department of English City, University of London. Overview. The MA Prose Fiction at UEA is the oldest and most prestigious Creative Writing programme in the UK. Uniquely focused on the writing of fiction
In this short film, Emma Healey, a graduate of our MA Creative Writing Prose Fiction and author of two very successful novels, talks about her writing. Opinion latest - The Daily Telegraph. Esperanto (/ ˌ ɛ s p ə ˈ r ɑː n t oʊ, -ˈ r æ n-/) is the most widely spoken constructed international auxiliary language. L. L. Zamenhof, a Polish-Jewish.
Course: MA Creative Writing Prose (Part time) - Springest. MA Creative Writing Prose Fiction at University Published authors teach our creative writing courses.
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POETRY WINNERS - Judge Lemn Sissay - Report 1st Siren Call - Mary-Jane Holmes, Middleton-in-Teesdale2nd River Climber - Simon Murphy.
Red Birds is the third novel by UEA alumnus Mohammed Hanif and is published in the UK by Bloomsbury this week. Mohammed graduated from the Prose Fiction. Many writers start with writing short stories before they move onto novel writing. But really, what's the difference between short story and novel writing. UEA Creative Writing Course - Wikipedia. Anna Davis Anna is the founder and Director of the Curtis Brown Creative writing school. She is the author of five novels, published around the world in 20 languages:.
Exactly a year and a few weeks ago I wrote a draft article to post on Awate in the form of a letter to Tzigereda. It was a kind of encouragement. MA Creative Writing Prose Fiction (Part Time) Postgraduate. UEA Creative Writing Course The course is split into four strands: Prose, Creative Non-Fiction, Kazuo Ishiguro (MA, 1980). Find out more about Postgraduate Courses in UEA's School of Literature, Drama and Creative Writing, or contact<EMAIL_ADDRESS>Up to £25,000 awarded.
The best opinions, comments and analysis from The Telegraph. Applications are now open for the Miles Morland Foundation African Scholarship 2018/2019. The Scholarship is awarded to a Postgraduate student within. Written by Andrew Posted in The Writing Life Tagged with creative writing courses, learning, MA's, teaching 15 comments. October 5, 2013 - 11:29 am Debbie. Black Rock Amanda Smyth on Amazon.com. FREE shipping on qualifying offers. Celia's mother died bringing her into the world - when one soul flies in, another flies. The Watchmaker of Filigree Street Natasha Pulley on Amazon.com. FREE shipping on qualifying offers. Watchmaker of Filigree Street. Literature, Drama and Creative Writing Scholarships 2017 Winners The Bridport Prize.


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Wednesday, June 5, 2013
Group 5: Amish Gala, Deyvid William, Pankaj Kapania, and Romeo Honvo
Statistics:
| Type | Measurement Phase 1 | Measurement Phase 2 |
|---|---|---|
| Total LOC | 3222 (43 classes) | 9633 (94 classes) |
| Total Production LOC | 2477 (29 classes) | 7292 (69 classes) |
| Total Unit Test LOC | 742 (14 classes, 40 unit tests, 7 integration tests) | 2341 (25 classes, 137 unit tests, 18 integration tests ) |
| Code Coverage (ALL) | 55.6% | 57.3% |
| Code Coverage (Unit) | 32.2% | 32.5% |
| Code Coverage (Integration) | 35.5% | 36.8% |
Phase 2 presented us with some new requirements to complement our already robust email client:
The package structure stayed the same. Classes were simply added to each tier
Email Template
The Email template class diagram is shown here. It is interesting to note that we have followed the same n-tier architecture as originally created. EmailFrame in the context of a Template (NEW, EDIT, APPLY) will know to call the correct service layer methods when actions are performed. Model layer classes to store templates and the collection of templates are provided, and they communicate with the persistence layer abstraction TemplateDao.
Note that the placeholder string looks like this: ${text_here}. Thus strings surrounded by this this are automatically selected.
Search Emails
Email interface was enhanced to implement a new Searchable interface. This allowed our application to treat emails as searchable, and thus call the "isMatch" method on them. The email delegated the responsibility to a new Search object which used regex to determine if there is a match. This separation of concerns and nice encapsulation allowed us to fully unit test the search feature (38 JUnit tests!) in isolation. The JTable object in the EmailClient main application was updated with the results, and users could then double click to open up a found email.
Rule Filters
Rule Filters, just like Templates and Meetings required us to build objects in each layer of our n-tier architecture. The communication between layers was respected, and we used View Entity objects to ensure that there was no direct coupling. RuleFrame is responsible to handle the new and edit functionality. RuleSettings is responsible to help the user organize all rules by having them visible all in one place, and given the ability to re-order them.
In order to realize the function of ordered rules, we decided to use a separate XML file to store the value of the latest rule. This allowed us to easily "query" for the next rule ID. Swap was enabled so that users could change the order of rules, and therefore influence how their emails would be affected when rules were executed.
Meetings
Meetings constructed as first-class citizens in our overall design - they are given their own independent UI, service, model and persistence objects, and the existing Folder architecture was adapted to handle displaying and manipulation of meetings. We needed to consider the operations such as create, edit, and cancel/delete. One thing we noticed was that the meeting view entity was quite large, and that perhaps we could encapsulate sub-features into their own objects (for example MeetingDates). This will be left as an exercise to the reader.
Problem: Template view looks almost exactly the same as Email view
Our design has Template reuse the same view class EmailFrame
. This at first seemed
like a good idea since Templates and Emails are very similar; however, towards the end of phase 2,
it became troublesome. In the end, we decided to live with this violation of SRP (EmailFrame can
be instantiated for both Emails and Template), because the benefit of reduced duplication outweighed
the other considerations.
Problem: how to support Meeting Objects and the fact that they need to be displayed in a folder in the UI.
Originally, Folder was an abstract class, with two children SystemFolder and UserFolder (to represent the different folders in our hierarchy of folders). Each Folder know about its contents - a generic collection of <Email>. With the introduction of Meetings, we needed to think long and hard about how to handle these new objects, since they too needed to be represented in some sort of containing folder. Our solution looked like this:
Essentially, we needed to push down SystemFolder and UserFolder in the inheritance hierarchy so that we could treat Folders containing Meetings and Folders containing Emails similarly. However, even this solution (being as clean as it was), still led to some headaches and "conditional logic" in our EmailClient main view class. Additionally, MeetingFolder and UserFolder shared some mutually exclusive methods, and we were forced to throw exceptions in the event that they were incorrectly called.
Problem: How to deal with searching special characters
CEC Application will not perform the search, ignoring user request, in the following cases:
The symbols "@", "." and "" are not considered Special characters but "Email characters".
The Email search engine finds emails that contains the user input in at least one of the fields: From, To, CC, Subject and Body. It considers every word separately, what means that the application will return Emails that match with at least one of the words informed by the user. Special characters are not considered, and words concatenated with them are treated separately.
Problem: how to support a nice flow of guided template usage so the user is delighted
This was a challenging endeavour. We first tried to manually parse the fields in a template, and build some sort of map of placeholders. This, coupled with the complexities of handling replacements in the text and responding to keyboard events resulted in quite a big headache. Eventually, after some research into using JTextArea and JTextFields, we decided that using javax.swing.InputMap and javax.swing.ActionMap was the best approach, and hid complexities in well encapsulated objects.
For the regex part, we designed an implemented a Placeholder Helper class, whose responsibility was to respond with the current start and end positions of the next available placeholder match.
Each field on which we wanted to apply the highlighting mechanism was asked to return its Input Map and Action Map. From there, we registered an input (in our case, either the Enter key, or the Tab key), and corresponding Action (in our case, to run an Abstract Action which we aptly named CommitAction). Commit Action took as input the field for which the input was performed, and then executed a simple method (action performed was called by the swing framework upon detection of the input):
Much of the complexity of dealing with the regex and positions was hidden nicely in the Placeholder Helper class. This allowed us to fully test some of the edge and corner cases before actually using the methods.
Problem: dealing with single rules, multiple rules, and overlapping rules
Our approach here was to make the application of rules as simple as possible. From the very beginning, we designed rules to work with the following constraints:
Currently our save policy does not check if saving a template with the same name will overwrite an existing template with the same name. This is
If the user opens the Rule Settings window, and proceeds to edit one rule, but then decides to cancel the operation, the UI will still show that the rule is selected on the JTable. But if the user decides to click Edit again, he is in for quite a surprise! The system responds with "Please select a rule to edit."
We wanted to try and use a Test Helper for some of the integration tests to handle some of the heavy lifting, and hide away some complexity from the test class itself. This was not completed in time.
We were unable to cleanup every single TODO left in the code. This is something which we should target before beginning the implementation task for Phase 3.


NumPyro Release We’re excited to announce the release of NumPyro, a NumPy-backed Pyro using JAX for automatic differentiation and JIT compilation, with over 100x speedup for HMC and NUTS! See the examples and documentation for more details.
Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling. It was designed with these key principles:
Universal: Pyro can represent any computable probability distribution.
Scalable: Pyro scales to large data sets with little overhead.
Minimal: Pyro is implemented with a small core of powerful, composable abstractions.
Flexible: Pyro aims for automation when you want it, control when you need it.
Check out the blog post for more background or dive into the tutorials.
If you use Pyro or NumPyro in your research, please consider citing our papers.
@article{bingham2018pyro, author = {Bingham, Eli and Chen, Jonathan P. and Jankowiak, Martin and Obermeyer, Fritz and Pradhan, Neeraj and Karaletsos, Theofanis and Singh, Rohit and Szerlip, Paul and Horsfall, Paul and Goodman, Noah D.}, title = {{Pyro: Deep Universal Probabilistic Programming}}, journal = {Journal of Machine Learning Research}, year = {2018} } @article{phan2019composable, author = {Phan, Du and Pradhan, Neeraj and Jankowiak, Martin}, title = {Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro}, journal = {arXiv preprint arXiv:1912.11554}, year = {2019} }
(Add yours too!)


Nirav Patel
Graduate student in Computer Science at
North Carolina State University
(Graduating Summer 2022).
Previously Software Engineer at
Juniper Networks
.


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library(tidyverse)
library(cowplot)
library(viridis)
library(knitr)
library(kableExtra)
knitr::opts_chunk$set(tidy.opts=list(width.cutoff=60),tidy=TRUE, echo = TRUE, message=FALSE, warning=FALSE, fig.align="center")
source("../../../IDA/tools/plotting_tools.R")
theme_set(theme_1())
This set of experiments is the next iteration from this previous set see this notebook. The idea was to use time resolved spectroscopy with well-characterized metal complexes to test whether biofilm eDNA could support DNA CT. Ultimately, we were looking for evidence of DNA CT in the form of ‘static quenching,’ which occurs when fluorophore quenching occurs on the extremely fast time scales expected for DNA CT. See this figure below, which shows the difference between static quenching and dynamic quenching.
knitr::include_graphics("../../08_07_19_biofilm_Ru_Rh/analysis/static_dynamic_quenching_fig.jpg")
The previous experiments suggested that we were seeing static quenching with \(Ru(phen)_2dppz^{2+}\) and \(Rh(phi)_2bpy^{3+}\) in resuspended colony biofilms. For this set of experiments we wanted to perform several controls to further test this result.
We tried all of the experiments above with the help of Eric Stemp and Nirit. Nirit did suggest one experiment that we were not able to try: determine if \(Rh(phi)_2bpy^{3+}\) quencher affects biofilm background signal in the absence of \(Ru(phen)_2dppz^{2+}\).
∆phz* biofilms were grown as normal for 5 days. Plates were a little more humid than usual, but colony morphology looked relatively normal. Six replicate biofilms were grown in a 6 well plate as shown below:
Colonies on membranes were placed in eppendorf tubes with 500uL of PBS 137mM NaCl, then vortexed for 1 min to resuspend. Membranes were removed and came out almost entirely clean as shown below.
Within 10 min of resuspension 400uL of the biofilm slurry was transferred to a cuvette:
Background scans were taken with the biofilm only, which exbited a signficant signal, although the \(Ru(phen)_2dppz^{2+}\) was clearly visible above this at 5uM (at 1uM it was barely visible). \(Ru(phen)_2dppz^{2+}\) was excited at 532nm and emission was recorded at 620nm. Other spectroscopic information is recorded in the header of each data file, but after data file 3 (rep 3) the exact same settings were used throughout.
A fresh LB plate of ∆phz* was streaked out the night before, and a 50mL flask of LB was inoculated on the morning of the experiment. After about 5hrs of growth the culture reached an OD of ~0.4, which was considered to be in the middle of exponential phase. In order to match the cell density of the biofilm suspension, the OD500 of the biofilm slurry was measured to be about 20. Therefore the liquid grown cells were concentrated ~50x by spinning down 24mL of culture and resuspending in 500uL of PBS 137. To the naked eye, the resuspended cells were quite opaque and of similar density.
A calf thymus DNA stock was diluted to 500uM nucleotides and 400uL was transferred to a cuvette.
Generally, the \(Ru(phen)_2dppz^{2+}\) and \(Rh(phi)_2bpy^{3+}\) were added to the cuvettes from 200uM stocks, although for quencher eq > ~6 \(Rh(phi)_2bpy^{3+}\) was added from a 1.5mM stock to avoid changing the volume dramatically. \(Ru(NH_3)_6\) (aka Ruthenium hexamine aka RuHex) was added from a similarly dilute stock for the low equivalents and from a 20mM? stock for the higher equivalents.
Metal complexes were added directly the cuvette, pipetted up and down 10-15 times and then the cuvette was shaken gently to ensure complete mixing. Measurements were taken immediately following.
First let’s read in all the data. We’ll start with the compressed version of the data, as Jay suggested. They worked fine last time.
# Functions modified from echem import to read in
# spectroscopy data
import_data <- function(filenames, file_paths, data_cols = c("time",
"intensity"), skip_rows = 16) {
# Adapted from echem_import() in /IDA/tools
files_df <- data_frame(filename = filenames) %>% mutate(file_contents = map(file_paths,
~read_csv(., col_names = data_cols, skip = skip_rows)))
files_df
}
unnest_df <- function(df, filename_cols, rep = F) {
# Adapted from echem_unnest_df() in /IDA/tools
df_unnested <- df %>% unnest(file_contents) %>% separate(filename,
filename_cols, sep = "_")
if (rep) {
df_unnested <- df_unnested %>% mutate(rep = as.integer(str_extract(rep,
"^[0-9]+")))
}
df_unnested
}
import_to_df <- function(filenames, file_paths, data_cols = c("time",
"intensity"), skip_rows = 16, filename_cols, rep = F) {
# Combine echem_import() and echem_unnest_df() into one
# function.
df <- import_data(filenames, file_paths, data_cols, skip_rows)
df_unnested <- unnest_df(df, filename_cols, rep)
df_unnested
}
data_path = "../data/compressed/"
data_cols <- c("time", "intensity")
skip_rows = 16
# Add 'reactor' to file name so it is parsed into column
filename_cols = c("date", "rep", "compressed")
data_names <- dir(path = data_path, pattern = ".+[dat]$")
# Add correct paths separate from filenames
data_paths <- data_names %>% paste(data_path, ., sep = "")
# Read in all SWVs with one function call
compressed_data <- import_to_df(filenames = data_names, file_paths = data_paths,
data_cols = data_cols, skip_rows = skip_rows, filename_cols = filename_cols,
rep = T)
compressed_data %>% head() %>% kable(digits = 10) %>% kable_styling(bootstrap_options = "condensed")
| date | rep | compressed | time | intensity |
|---|---|---|---|---|
| 82919 | 10 | compressed.dat | -9.94e-08 | 2.03066e-04 |
| 82919 | 10 | compressed.dat | -9.78e-08 | -2.25840e-04 |
| 82919 | 10 | compressed.dat | -9.56e-08 | -1.34819e-05 |
| 82919 | 10 | compressed.dat | -9.34e-08 | 2.57582e-05 |
| 82919 | 10 | compressed.dat | -9.12e-08 | 3.67667e-05 |
| 82919 | 10 | compressed.dat | -8.91e-08 | -5.19785e-04 |
You can see that we have a file “rep” (i.e. ID number) and intensity vs. time data. There are about 63 files, so I’m going to write out the metadata in excel and merge it in so I don’t have to split up the different experiments manually. Here’s what the metadata look like:
metadata <- read_csv("../data/08_29_19_spectroscopy_metadata.csv") %>%
group_by(material, material_id) %>% mutate(run = rep - min(rep) +
1) %>% mutate(exp_num = group_indices())
df <- left_join(compressed_data, metadata, by = "rep")
metadata %>% kable() %>% kable_styling(bootstrap_options = "condensed") %>%
scroll_box(width = "100%", height = "400px")
| rep | material | material_id | ruphen_conc | quencher_conc | quencher_eq | quencher_id | comment | run | exp_num |
|---|---|---|---|---|---|---|---|---|---|
| 5 | biofilm | 1 | 0 | 0 | NA | Rh | NA | 1 | 1 |
| 6 | biofilm | 1 | 1 | 0 | 0 | Rh | NA | 2 | 1 |
| 7 | biofilm | 1 | 1 | 0 | 0 | Rh | NA | 3 | 1 |
| 8 | biofilm | 1 | 5 | 0 | 0 | Rh | NA | 4 | 1 |
| 9 | biofilm | 1 | 5 | 5 | 1 | Rh | NA | 5 | 1 |
| 10 | biofilm | 1 | 5 | 10 | 2 | Rh | NA | 6 | 1 |
| 11 | biofilm | 1 | 5 | 20 | 4 | Rh | NA | 7 | 1 |
| 12 | biofilm | 1 | 5 | 40 | 8 | Rh | NA | 8 | 1 |
| 13 | biofilm | 2 | 0 | 0 | NA | Rh | NA | 1 | 2 |
| 14 | biofilm | 2 | 5 | 0 | 0 | Rh | NA | 2 | 2 |
| 15 | biofilm | 2 | 5 | 5 | 1 | Rh | NA | 3 | 2 |
| 16 | biofilm | 2 | 5 | 10 | 2 | Rh | NA | 4 | 2 |
| 17 | biofilm | 2 | 5 | 15 | 3 | Rh | NA | 5 | 2 |
| 18 | biofilm | 2 | 5 | 20 | 4 | Rh | NA | 6 | 2 |
| 19 | biofilm | 2 | 5 | 30 | 6 | Rh | NA | 7 | 2 |
| 20 | biofilm | 2 | 5 | 40 | 8 | Rh | NA | 8 | 2 |
| 21 | biofilm | 2 | 5 | 50 | 10 | Rh | NA | 9 | 2 |
| 22 | biofilm | 2 | 5 | 60 | 12 | Rh | NA | 10 | 2 |
| 39 | biofilm | 2 | 5 | 60 | 12 | Rh | 1 hr later | 27 | 2 |
| 23 | liquid_cells | 1 | 0 | 0 | NA | Rh | NA | 1 | 7 |
| 24 | liquid_cells | 1 | 5 | 0 | 0 | Rh | NA | 2 | 7 |
| 25 | liquid_cells | 1 | 5 | 5 | 1 | Rh | NA | 3 | 7 |
| 26 | liquid_cells | 1 | 5 | 10 | 2 | Rh | NA | 4 | 7 |
| 27 | liquid_cells | 1 | 5 | 20 | 4 | Rh | NA | 5 | 7 |
| 28 | biofilm | 3 | 0 | 0 | NA | RuHex | NA | 1 | 3 |
| 29 | biofilm | 3 | 5 | 0 | 0 | RuHex | NA | 2 | 3 |
| 30 | biofilm | 3 | 5 | 5 | 1 | RuHex | NA | 3 | 3 |
| 31 | biofilm | 3 | 5 | 10 | 2 | RuHex | NA | 4 | 3 |
| 32 | biofilm | 3 | 5 | 20 | 4 | RuHex | NA | 5 | 3 |
| 33 | biofilm | 3 | 5 | 40 | 8 | RuHex | NA | 6 | 3 |
| 34 | biofilm | 3 | 5 | 80 | 16 | RuHex | NA | 7 | 3 |
| 35 | biofilm | 3 | 5 | 120 | 24 | RuHex | NA | 8 | 3 |
| 36 | biofilm | 3 | 5 | 160 | 32 | RuHex | NA | 9 | 3 |
| 37 | biofilm | 3 | 5 | 200 | 40 | RuHex | NA | 10 | 3 |
| 38 | biofilm | 3 | 5 | 500 | 100 | RuHex | NA | 11 | 3 |
| 40 | biofilm | 4 | 0 | 0 | NA | none | NA | 1 | 4 |
| 41 | biofilm | 4 | 5 | 0 | 0 | none | NA | 2 | 4 |
| 42 | biofilm | 4 | 5 | 0 | 0 | none | NA | 3 | 4 |
| 43 | biofilm | 4 | 5 | 0 | 0 | none | NA | 4 | 4 |
| 44 | biofilm | 4 | 5 | 0 | 0 | none | NA | 5 | 4 |
| 54 | biofilm | 4 | 5 | 0 | 0 | none | 15 min later | 15 | 4 |
| 45 | biofilm | 5 | 0 | 0 | NA | Rh | NA | 1 | 5 |
| 46 | biofilm | 5 | 10 | 0 | 0 | Rh | NA | 2 | 5 |
| 47 | biofilm | 5 | 10 | 10 | 1 | Rh | NA | 3 | 5 |
| 48 | biofilm | 5 | 10 | 20 | 2 | Rh | NA | 4 | 5 |
| 49 | biofilm | 5 | 10 | 30 | 3 | Rh | NA | 5 | 5 |
| 50 | biofilm | 5 | 10 | 40 | 4 | Rh | NA | 6 | 5 |
| 51 | biofilm | 5 | 10 | 60 | 6 | Rh | NA | 7 | 5 |
| 52 | biofilm | 5 | 10 | 80 | 8 | Rh | NA | 8 | 5 |
| 53 | biofilm | 5 | 10 | 100 | 10 | Rh | NA | 9 | 5 |
| 55 | ctDNA | 1 | 0 | 0 | NA | Rh | 500uM nucleotides | 1 | 6 |
| 56 | ctDNA | 1 | 5 | 0 | 0 | Rh | NA | 2 | 6 |
| 57 | ctDNA | 1 | 5 | 5 | 1 | Rh | NA | 3 | 6 |
| 58 | ctDNA | 1 | 5 | 10 | 2 | Rh | NA | 4 | 6 |
| 59 | ctDNA | 1 | 5 | 15 | 3 | Rh | NA | 5 | 6 |
| 60 | ctDNA | 1 | 5 | 20 | 4 | Rh | NA | 6 | 6 |
| 61 | ctDNA | 1 | 5 | 30 | 6 | Rh | NA | 7 | 6 |
| 62 | ctDNA | 1 | 5 | 40 | 8 | Rh | NA | 8 | 6 |
| 63 | ctDNA | 1 | 5 | 50 | 10 | Rh | NA | 9 | 6 |
As described above you can see that we varied a good number of parameters. I’ll generate the background subtractions and normalizations, because I know we will want to look at those. Note that background subtraction is simply subtracting the minimum value at each time point, not necessarily the biofilm only scan - we’ll come back to this.
df_bg <- df %>% group_by(material, material_id, time) %>% mutate(min = min(intensity)) %>%
mutate(bg_sub = intensity - min)
df_biofilm_bg <- df %>% group_by(material, material_id, time) %>%
mutate(min = min(ifelse(run == 1, intensity, NA), na.rm = T)) %>%
mutate(bg_sub = intensity - min)
df_bg_norm <- df_bg %>% filter(time > 0) %>% group_by(material,
material_id, run) %>% mutate(max = max(bg_sub)) %>% mutate(norm_intensity = bg_sub/max)
Now, let’s walk through the experiments chronologically.
Note that runs 1 - 3 for experiment 1 were done on a larger scale with 1uM Ru, which was not really visible. So, we moved up to 5uM Ru starting with run 4. Here’s what the data looks like from here (we don’t have a great biofilm only control):
ggplot(df %>% filter(exp_num == 1 & run >= 4), aes(x = time,
y = intensity, color = factor(quencher_eq))) + geom_path() +
xlim(NA, 5e-07)
Here you can see that the raw signal does seem to change as we added the \(Rh(phi)_2bpy^{3+}\). If we background subtract from the minimum value it looks like this:
ggplot(df_bg %>% filter(exp_num == 1 & run >= 4), aes(x = time,
y = bg_sub, color = factor(quencher_eq))) + geom_path() +
xlim(NA, 5e-07)
Note that this is kinda messed up, because it’s just background subtract from the lowest value, which in this case is run 8…not the biofilm only control. That said, it looks like static quenching.
Let’s see if the normalized curves have the same shape (and therefore lifetime):
ggplot(df_bg_norm %>% filter(exp_num == 1 & run >= 4), aes(x = time,
y = norm_intensity, color = factor(quencher_eq))) + geom_path() +
xlim(NA, 5e-07)
So again, it’s a little wild, because we’ve background subtracted with run 8, but the first few runs seems to overlay well, suggesting that they exhibit similar lifetimes.
This next condition was basically a better version of biofilm 1. Let’s look at the raw data:
ggplot(df %>% filter(exp_num == 2), aes(x = time, y = intensity,
color = quencher_eq)) + geom_path(data = df %>% filter(exp_num ==
2 & ruphen_conc == 0), color = "gray", size = 3) + geom_path() +
xlim(NA, 5e-07)
Here I’ve highlighted the biofilm only control in gray. You can see that it is basically the same as the highest quencher concentrations. Let’s see how the background subtraction looks if we subtract from the biofilm only control:
ggplot(df_biofilm_bg %>% filter(exp_num == 2), aes(x = time,
y = bg_sub, color = quencher_eq)) + geom_path(data = df_biofilm_bg %>%
filter(exp_num == 2 & ruphen_conc == 0), color = "gray",
size = 3) + geom_path() + xlim(NA, 5e-07)
And now let’s just subtract from the minimum value:
ggplot(df_bg %>% filter(exp_num == 2), aes(x = time, y = bg_sub,
color = quencher_eq)) + geom_path(data = df_bg %>% filter(exp_num ==
2 & ruphen_conc == 0), color = "gray", size = 3) + geom_path() +
xlim(NA, 5e-07)
Again, the biofilm only control is highlighted in gray. Here you can see that unfortunately the biofilm only sample is not the lowest intensity signal, meaning that the quenched signal is actually lower in certain places than the biofilm alone. Background subtracting from the biofilm only control yields weird results, so this is where Nirit’s suggestion may come in…maybe we should have background subtracted from a biofilm + \(Rh(phi)_2bpy^{3+}\) control or maybe we should just be fine background subracting from the lowest value. Not sure what the best practice would be here.
That said, if we just background subtract from the lowest value, it looks like pretty good static quenching…let’s see how the normalization looks:
# Excluding the highest quencher concentration, because that
# was bg_sub
ggplot(df_bg_norm %>% filter(exp_num == 2 & quencher_conc < 60),
aes(x = time, y = norm_intensity, color = quencher_eq)) +
geom_path(data = df_bg_norm %>% filter(exp_num == 2 & ruphen_conc ==
0), color = "gray", size = 3) + geom_path() + xlim(NA,
5e-07)
It’s not perfect, but the shapes look pretty similar. The only obviously different one is the background only signal (highlighted in gray).
Remember, this condition was to assess whether cells (containing genomic DNA) were sufficient to give the strong static quenching signal. If yes, that would suggest the metal complexes enter the cell and the signal could come from gDNA. If no, that suggests the signal is specific to extracellular DNA. Let’s look at the raw data:
ggplot(df %>% filter(exp_num == 7), aes(x = time, y = intensity,
color = factor(run))) + geom_path() + xlim(NA, 5e-07)
So, all the runs look almost identical. Run 1 is biofilm only, Run 2 is + \(Ru(phen)_2dppz^{2+}\) , and Runs 3,4,and 5 add increasing \(Rh(phi)_2bpy^{3+}\). This is already pretty clear…there’s barely any signal from the \(Ru(phen)_2dppz^{2+}\), which only emits when it is bound to DNA. Therefore, this data suggests that the complex is not bound to DNA when incubated with the liquid grown cells…and so the signal probably isn’t coming from gDNA. Because there’s basically no signal, we don’t expect to see much quenching, but here’s what the background subtraction looks like:
ggplot(df_bg %>% filter(exp_num == 7), aes(x = time, y = bg_sub,
color = factor(run))) + geom_path() + xlim(NA, 5e-07)
Maybe there’s a tiny \(Ru(phen)_2dppz^{2+}\) signal (blue run 2) that is quenched, but it’s super noisy and I don’t think that really matters.
Next we tried a different quencher, that should not be capable of fast DNA CT. In vitro this quencher should cause dynamic quenching (see intro), but Eric did express some concern that we may not see any quenching if RuHex binding were strongly inhibited by the extra NaCl in the buffer (137mM)…so we weren’t sure what to expect. Here’s the raw data:
ggplot(df %>% filter(exp_num == 3), aes(x = time, y = intensity,
color = quencher_eq)) + geom_path() + xlim(NA, 5e-07)
The biofilm only background is in gray and the RuHex equivalents are shown as colors. You can see the signal does change a little bit at the higher concentrations, but it’s hard to tell. Here’s the background subtraction:
ggplot(df_bg %>% filter(exp_num == 3), aes(x = time, y = bg_sub,
color = quencher_eq)) + geom_path() + xlim(NA, 5e-07)
Here the background subtraction mainly worked as intended, although you can see at short times > 0 the gray line is non zero. It looks like the signal did change upon addition of RuHex, but it’s not really clear whether it’s static or dynamic type quenching…and it’s a little noisy.
If we normalize it looks like this:
ggplot(df_bg_norm %>% filter(exp_num == 3), aes(x = time, y = norm_intensity,
color = quencher_eq)) + geom_path() + xlim(NA, 5e-07)
Still very noisy…but the curves look like mostly the same shape to me. Let’s try normalizing by a slightly later timepoint when the background subtraction is perfect:
df_bg_norm_2 <- df_bg %>%
filter(time > 2.5e-8) %>% #Changed this number to be slightly > 0
group_by(material, material_id, run) %>%
mutate(max = max(bg_sub)) %>%
mutate(norm_intensity = bg_sub / max)
ggplot(df_bg_norm_2 %>% filter(exp_num ==3), aes(x = time, y = norm_intensity, color = quencher_eq)) +
geom_path() + xlim(NA, 5e-7)
Now the decay looks really identical, suggesting more of a static quenching… That said, the quenching was a little noisy / weak, and probably not as clear cut as the \(Rh(phi)_2bpy^{3+}\). Perhaps at lower salt concentrations we would see something different.
This condition was to test whether the \(Ru(phen)_2dppz^{2+}\) emission was changing over time. If strong changes were observed that could suggest the ‘quenching’ we observed was an artifact, or that the metal complex was slowly getting inside the cell or causing lysis.
Here’s the data:
ggplot(df %>% filter(exp_num == 4), aes(x = time, y = intensity,
color = factor(run))) + geom_path() + xlim(NA, 5e-07)
Looks pretty clear cut from here. Run 1 was the biofilm only and runs 2,3,4,5, and 15 were subsequent scans of the same cuvette. Run 15 was taken an additional 15 min after run 5. There seems to be no change in the signal.
Here’s the background subtraction:
ggplot(df_bg %>% filter(exp_num == 4), aes(x = time, y = bg_sub,
color = factor(run))) + geom_path() + xlim(NA, 5e-07)
Run 15, might have a slightly higher signal than the others pointing to toxicity or cell permeability given longer times, but almost all experiments were conducted within the amount of time it took to reach run 5.
Note that without the quencher and good background subtraction from the biofilm only control, the \(Ru(phen)_2dppz^{2+}\) is only about 0.015 as opposed to 0.04 for biofilms 1 and 2. To me that suggests the quenched samples in the first two really are quenching the signal to be significantly less than the biofilm only control…
Here’s the normalization:
ggplot(df_bg_norm %>% filter(exp_num == 4), aes(x = time, y = norm_intensity,
color = factor(run))) + geom_path() + xlim(NA, 5e-07)
Same shape as expected. This plot also gives us a sense of the variability in shape of the \(Ru(phen)_2dppz^{2+}\) emission. Considering this, some of the earlier biofilm data with quencher looks pretty good.
To try to get a stronger signal, we also tried a biofilm with double the concentration of metal complexes:
ggplot(df %>% filter(exp_num == 5), aes(x = time, y = intensity,
color = quencher_eq)) + geom_path(data = df %>% filter(exp_num ==
5 & ruphen_conc == 0), color = "gray", size = 3) + geom_path() +
xlim(NA, 5e-07)
Here the biofilm only control is highlighted in gray. We can see a strong signal and strong quenching. Let’s look at the background subtraction:
ggplot(df_bg %>% filter(exp_num == 5), aes(x = time, y = bg_sub,
color = quencher_eq)) + geom_path(data = df_bg %>% filter(exp_num ==
5 & ruphen_conc == 0), color = "gray", size = 3) + geom_path() +
xlim(NA, 5e-07)
As for the 5uM condition, we see what appears to be static quenching, although again the biofilm only background is not actually the lowest signal. Let’s normalize:
ggplot(df_bg_norm %>% filter(exp_num == 5 & quencher_eq < 10),
aes(x = time, y = norm_intensity, color = quencher_eq)) +
geom_path(data = df_bg_norm %>% filter(exp_num == 5 & ruphen_conc ==
0), color = "gray", size = 3) + geom_path() + xlim(NA,
5e-07)
Interestingly, here we see that the curves do seem to have different shapes. Perhaps at this concentration of \(Ru(phen)_2dppz^{2+}\) we are seeing a combination of static and dynamic quenching.
The last condition we tried was in vitro with the same concentration of metal complexes as before with calf thymus DNA. here’s the data:
ggplot(df %>% filter(exp_num == 6), aes(x = time, y = intensity,
color = quencher_eq)) + geom_path(data = df %>% filter(exp_num ==
6 & ruphen_conc == 0), color = "gray", size = 3) + geom_path() +
xlim(NA, 5e-07)
Wow, here we see a super strong signal that is quenched very well. The biggest difference is actually that the in vitro cuvette has basically no background emission (gray). Let’s look at the background subtraction:
ggplot(df_bg %>% filter(exp_num == 6), aes(x = time, y = bg_sub,
color = quencher_eq)) + geom_path(data = df_bg %>% filter(exp_num ==
6 & ruphen_conc == 0), color = "gray", size = 3) + geom_path() +
xlim(NA, 5e-07)
Looks like pretty strong static quenching.
This also gives us a feeling for how much of the metal complexes are bound by DNA in our biofilms. The max signal in the biofilm is about 0.04, suggesting that the eDNA concentration or solution conditions may be limiting DNA binding a little bit.
Here’s the normalized curves:
ggplot(df_bg_norm %>% filter(exp_num == 6 & ruphen_conc > 0),
aes(x = time, y = norm_intensity, color = quencher_eq)) +
geom_path() + xlim(NA, 5e-07)
Again, interesting. The curves are not the exact same shape, even though the background subtraction here is almost perfect. This suggests that there may be some dynamic quenching in addition to the strong static quenching.
Overall, I think this set of experiments was quite helpful. As far as whether we are truly observing DNA CT based static quenching I have a few feelings:
Reassuring that:
Slightly concerning that:
Ultimately, I think the static quenching is real. I think that the whole static vs. dynamic quenching is not super clear cut and that tossing in the biofilm background signal makes it a little messier. According to the past papers, the static quenching indicates DNA CT. This result is really to be expected I think, although it is nice to know. What we are really testing here is - is eDNA intact enough to support DNA CT between these two metal complexes? We always assumed it was, because you can do PCR and restriction digest etc just like genomic DNA. Therefore, this data really suggests that the eDNA is relatively intact and not full of abasic sites and falling apart etc.
sessionInfo()
## R version 3.5.2 (2018-12-20)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.6
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## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
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## locale:
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## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## other attached packages:
## [1] kableExtra_1.0.1 knitr_1.23 viridis_0.5.1
## [4] viridisLite_0.3.0 cowplot_0.9.4 forcats_0.3.0
## [7] stringr_1.3.1 dplyr_0.8.1 purrr_0.2.5
## [10] readr_1.3.1 tidyr_0.8.2 tibble_2.1.3
## [13] ggplot2_3.2.0 tidyverse_1.2.1
##
## loaded via a namespace (and not attached):
## [1] tidyselect_0.2.5 xfun_0.7 haven_2.0.0 lattice_0.20-38
## [5] colorspace_1.4-0 generics_0.0.2 htmltools_0.3.6 yaml_2.2.0
## [9] rlang_0.3.4 pillar_1.3.1 glue_1.3.1 withr_2.1.2
## [13] modelr_0.1.2 readxl_1.2.0 munsell_0.5.0 gtable_0.2.0
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## [21] highr_0.7 broom_0.5.1 Rcpp_1.0.1 scales_1.0.0
## [25] backports_1.1.3 formatR_1.5 webshot_0.5.1 jsonlite_1.6
## [29] gridExtra_2.3 hms_0.4.2 digest_0.6.18 stringi_1.2.4
## [33] grid_3.5.2 cli_1.0.1 tools_3.5.2 magrittr_1.5
## [37] lazyeval_0.2.1 crayon_1.3.4 pkgconfig_2.0.2 xml2_1.2.0
## [41] lubridate_1.7.4 assertthat_0.2.1 rmarkdown_1.13 httr_1.4.0
## [45] rstudioapi_0.9.0 R6_2.4.0 nlme_3.1-140 compiler_3.5.2